1. Field of the Invention
The present invention relates generally to unresolved target detection using an infrared focal plane array and matched filters, and it more particularly relates to an unresolved target detection technique using multiple matched filters.
2. Description of the Related Art
With the advancement of IR FPA manufacturing technology, IR FPA has been broadly used for sensors in all three major platforms: airborne sensing, satellite sensing, as well as ground sensing. For example, passive IR (Infrared) sensors are widely used to detect the energy emitted from targets, backgrounds, incoming threats, and the atmosphere for a plurality of applications including military surveillance, missile target and detection systems, crop and forest management, weather forecasting, and other applications.
U.S. patent application Ser. No. 10/395,269, by Hai-Wen Chen and Teresa Olson, entitled “Integrated Spatio-Temporal Multiple Sensor Fusion System Design” provides a theoretical evaluation for different averaging processes that can reduce random noise and enhance target signatures. The inventor is a coauthor of several related papers including Hai-Wen Chen and Teresa Olson, “Integrated Spatio-Temporal Multiple Sensor Fusion System Design,” SPIE AeroSense, Proceedings of Sensor and Data Fusion Conference, vol. 4731, pp. 204-215, Orlando, Fla., 1-5 Apr., 2002; Hai-Wen Chen and Teresa Olson, “Adaptive Spatiotemporal Multiple Sensor Fusion,” Journal of Optical Engineering, vol. 42 (5), pp. 1481-1495, May, 2003.
The Matched Filter (MF) method is currently a popular approach for unresolved target detection using IR FPAs as sensor detectors. In the MF method, DPSF (discrete point spread function sampled by discrete pixels in IR FPA) is estimated from CPSF (continuous point spread function). CPSF is available based on the sensor optical and lens designs. A matched spatial filter is obtained by dividing the DPSF with the co-variance matrix of background clutter. This matched filter is optimal in an MSE (mean-square-error) sense in that it provides a maximum SCNR (signal to clutter noise ratio) for a point source (unresolved) target.
In current advanced optical designs, most energy of a DPSF can be contained within a 3×3 pixel area, and the PVF (point visibility function) can be as high as 0.6˜0.75. A 0.7 PVF means that if the peak of a CPSF is located at the center of a pixel, this pixel will contain 70% of the energy of the CPSF and 30% of its energy is spread out in the neighbor pixels. Although CPSF is a symmetrical Mexican-hat shape function, the shape of a DPSF varies depending on the spatial phases. Spatial phase means the location of the CPSF peak at the sub-pixel space. If the peak is aligned with the center of a pixel, we call it a center phase. Similarly, a corner phase means that the peak falls down on a corner of a pixel. In this case, all the four pixels nearby that corner will receive equal energy from the CPSF. Therefore, it is clear that a 3×3 DPSF of a center phase has a totally different shape of energy distribution from a 3×3 DPSF of a corner phase, as evidenced in FIGS. 2(a) and (b). The PVF of the CPSF is 0.73.
Theoretically there are infinite different phases. In practice, we can approximate the infinite phases by dividing a pixel into multiple sub-pixels. For example, if we divide a pixel into 11×11 sub-pixels, then we have 121 different phases to approximate all the infinite phases. At any time moment, any sub-pixel location should have an equal probability to be aligned with the CPSF peak. That is, the spatial phase is a random variable with a uniform distribution.
From the discussion above, it is clear that the random phase causes problems in target detection using the MF method. In the traditional MF method approach, the DPSF of center phase (or averaged phase) is used to obtain the matched filter. Therefore, if the target center is located near the center of a pixel, the MF method performs well. However, if the target center is located near pixel corners or edges, the performance will be worse because the matched filter is not matched to the DPSF of the corner (or edge) phase.
Accordingly, there is a need to improve target detection of a point source target, when utilizing a matched filter and when the target center is located away from the pixel center.